PERFORMANCE COMPARISON OF DYNAMIC POLICIES FOR REMOTE CACHING

In a distributed system, data servers (file systems and databases) can easily become bottlenecks. We propose an approach to offloading data access requests from overloaded data servers to nodes that are idle or less busy. This approach is referred to as remote caching, and the idle or less busy nodes are called mutual servers as they help out the busy server nodes on data accesses. In addition to server and client local caches, frequently accessed data are cached in the main memory or mutual servers, thus improving the data access time In the system. We evaluate several data propagation strategies among data servers and mutual servers. These include policies in which senders are active/passive and receivers are active/passive in initiating data propagation. For example, an active sender takes the initiative to offload data onto a passive receiver. Simulation results show that the active-sender/passive-receiver policy is the method of choice in most cases. Active-Sender policies are best able to exploit the main memory of other idle nodes in the expected normal condition where some nodes are overloaded and others are less loaded. All active polices perform far better than the policy without remote caching even in the degenerated case where each node is equally loaded.